Linganisha mbinu

	Uchanganuzi wa Tabaka za Siri za Kibayes (BLCA)	Uchanganuzi wa Kimfumo wa Uhakiki wa Kibayes (BCFA)
Nyanja	Takwimu	Saikometriki
Familia	Latent structure	Latent structure
Mwaka wa asili	1990s–2000s	2007–2012
Mwanzilishi	Lazarsfeld (classical LCA); Bayesian formulation developed through Cheeseman & Stutz (1996) and Dunson & Xing (2009)	Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov
Aina	Bayesian latent variable / finite mixture model	Bayesian latent variable model
Chanzo asilia	Dunson, D. B. & Xing, C. (2009). Nonparametric Bayes modeling of multivariate categorical data. Journal of the American Statistical Association, 104(487), 1042–1051.	Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232
Majina mbadala	Bayesian LCA, BLCA, Bayesian mixture of multinomials, Bayesian finite mixture model	BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA
Zinazohusiana	6	4
Muhtasari	Bayesian latent class analysis extends classical LCA by placing prior distributions on all model parameters and using posterior inference — typically via MCMC — to classify individuals into unobserved categorical groups, quantify uncertainty around class membership, and select the number of classes in a principled, probabilistic way.	Bayesian confirmatory factor analysis tests a pre-specified factor structure using Bayesian inference. Instead of point estimates with p-values, it produces full posterior distributions for loadings, factor correlations, and residual variances, allowing the researcher to incorporate prior knowledge and propagate parameter uncertainty naturally.